A Vehicle Mass Estimation Method Considering Shifting Factors

Abstract

The invention discloses a vehicle mass estimating method considering the gear-shifting factor. Firstly, vehicle driving state data are collected and calculated, and parameters needed for a model are obtained; then, the mechanical property in the vehicle driving process is combined to build a vehicle longitudinal dynamics model; a weighting least square recurrence mass estimating model with multiple forgetting factors is built; and the using condition of a vehicle mass real-time estimating system is determined, collected vehicle driving state data and relevant model parameters are input into the vehicle mass real-time estimating system, and the real-time vehicle mass is estimated and output. According to the vehicle mass estimating method considering the gear-shifting factor, a relatively accurate mass estimating result is obtained before and after gear shifting of the vehicle. Meanwhile, in consideration of the sudden change of the transmission ratio at the time of gear shifting and the change of a vehicle rotating mass conversion coefficient after gear shifting, a weighting least square recurrence estimating method with the multiple forgetting factors is adopted, and real-time estimating of the vehicle mass is achieved.

Description

technical field [0001] The invention relates to the technical field of real-time estimation of vehicle mass, in particular to a vehicle mass estimation method considering gear shifting factors. Background technique [0002] Real-time estimation of vehicle dynamics model parameters is the basis of vehicle control, and vehicle mass parameters are important parameters in vehicle dynamics models. Accurate and real-time vehicle mass estimation parameters can effectively improve the performance of vehicle electronic control systems, such as electronic stability control systems (ESP) relies on vehicle quality parameters to calculate the side slip angle and yaw angle of the center of mass in real time, so as to realize the control of the lateral slip of the vehicle. At the same time, studies have shown that adjusting the shift schedule according to real-time changes in quality parameters can save fuel by about 2.62%-4.86%. Therefore, accurate estimation of vehicle mass parameters i...

AI Technical Summary

Problems solved by technology

[0003] In the existing literature, the methods for estimating vehicle quality parameters can be divided into two categories. One is the sensor-based quality estimation method. This method needs to install corresponding sensors in the vehicle, which takes up space in the vehicle and improves the efficiency. The production cost of the vehicle is difficult to meet the actual application requirements; the other is the vehicle quality estimation method based on the vehicle CAN bus data, which is based on the vehicle longitudinal dynamics model and does not require additional sensors, which has good application convenience

However, since the vehicle needs to shift gears frequently during normal driving, the dynamic state of the vehicle during the gear shifting process cannot be described by the vehicle longitudinal dynamics model, and the rotational mass conversion coefficient of the vehicle longitudinal dynamics model will change before and after shifting, As a result, there is a large deviation in the vehicle mass estimation results after the shift behavior occurs, which seriously affects the vehicle mass estimation results and reduces the accuracy of the vehicle mass estimation.

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